Confusion from Profusion: Decision Making with Many Options

描述（由申请人提供）：美国人在健康和药物保险计划中有许多选择。这对于Medicare Part D药物覆盖计划来说尤其如此。增加选择通常与更大的机会，一个可用的选项将最好地满足个人的特定需求，但丰富的选择可能会导致混乱，并导致选择错误。这个项目的目的是更好地理解为什么个人在面对复杂的决策时往往做出糟糕的选择，并提出指导方针和选择界面设计，以提高个人的决策表现。我们的实验方法是量化的频率和幅度的选择错误时，个人被要求从一组竞争计划中选择最佳的计划。这一决定非常类似于在包括某些药物但不包括其他药物的药物计划中进行选择的任务，但也普遍适用于其他健康计划的选择。所提出的实验界面将向每个受试者呈现一系列矩阵，每个矩阵显示每个选择选项的属性（类似于覆盖和未覆盖的药物的集合）（即，所有可用的D部分药物计划）。实验对象将被要求从现有的选项中选择最佳方案，并将根据其选择的准确性获得经济补偿。我们将系统地研究受试者的决策如何受到他们所面临问题的复杂性的影响。此外，实验界面的变化将测试有关人们如何处理信息和做出复杂选择的竞争行为理论，从而导致决策模型的开发，从而可以测试改进的格式。实验设计的核心将是仔细调查决策敏锐度作为人口因素的函数，包括教育水平，性别，特别是年龄（初步工作表明，老年人在复杂环境中表现不佳）。受试者将通过亲自访问老年人的设施和电子从一个非常大的人口多样化的在线实验经济学主题池招募。将测量受试者汇总之间的差异以及补偿金额对受试者表现的影响。项目成果将包括向决策者提出建议，说明如何安排复杂的选择，以尽量减少选择错误。因此，表现不佳的群体可以在医疗保险和药物覆盖方面做出更好的选择，改善老年人的健康状况。项目叙述：这个项目的目标是进一步了解当人们遇到复杂的决策时，例如在选择医疗保健和药物覆盖计划时，可能会出现错误。这项研究将探讨一般人群和表现较差的亚群体之间决策敏锐度的潜在差异，可能与教育水平，性别，特别是年龄有关。研究结果将包括重组决策集的建议，以使表现不佳的群体，特别是老年人，作出更好的长期选择，改善自己的健康结果。

DESCRIPTION (provided by applicant): Americans have many alternatives among health and drug coverage plans. This is particularly true for Medicare Part D drug coverage plans. Increased choice usually correlates with a greater chance that an available option will best meet the particular needs of an individual, but an abundance of options may cause confusion and lead to selection errors. The aim of this project is to better understand why individuals often make poor choices when faced with complex decisions, and to suggest guidelines and selection interface designs that improve individuals' decision-making performance. Our experimental approach is to quantify the frequency and magnitude of selection errors when individuals are asked to choose the optimal plan from among a set of competing plans. This decision closely mimics the task of choosing among drug plans that include coverage for some drugs but not others, but also applies generally to other health plan selection choices. The proposed experiment interface will present each subject with a series of matrices each showing the attributes (analogous to the set of covered and not covered drugs) of each selection option (i.e., all available Part D drug plans). Experimental subjects will be asked to select the best plan from among the available options, and will be financially compensated in proportion to the accuracy of their selections. We will systematically examine how subjects' decisions are affected by the complexity of the problems they are facing. Also, variations in the experimental interface will test competing behavioral theories about how people process information and make complex choices, leading the development of a decision-making model against which improved formats can be tested. Central to the experimental design will be a careful investigation of decision-making acumen as a function of demographic factors including education level, sex, and especially age (preliminary work has demonstrated seniors under-perform substantially in complex settings). Subjects will be recruited via in-person visits to seniors' facilities and electronically from among a very large demographically-diverse on-line experimental economics subject pool. Differences among the subject pools and the effect of compensation amount on subject performance will be measured. Project outcomes will include recommendations to policy-makers on structuring complex choices to minimize selection errors. As a result, under-performing groups could be enabled to make better choices about health insurance and drug coverage, improving health outcomes of seniors. Project Narrative: The goal of this project is to further our understanding of the potential for error when people encounter complex decisions, as in the selection of health care and drug coverage plans. This study will examine underlying differences in decision-making acumen between the general population and more poorly performing sub-groups, possibly relating to education level, sex, and especially age. Study outcomes will include recommendations for restructuring decision sets to enable under-performing groups, especially seniors, to make better long-term choices improving their own health outcomes.